# AWS Step Functions AWS Step Functions is a serverless workflow orchestration service for building and coordinating distributed applications through visual workflows, service integration, error handling, and state management. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Build a serverless PII redaction pipeline with Amazon Bedrock Data Automation DevFeed: [Build a serverless PII redaction pipeline with Amazon Bedrock Data Automation]() Original publisher: [Read original article]() Author: Samantha Stuart Published: 2026-09-16T15:17:37Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [Amazon Bedrock](), [pii](), [Serverless](), [AWS Lambda](), [AWS Step Functions](), [Artificial Intelligence](), [Amazon Web Services](), [Ansible]() Tags: [advanced-300](), [amazon-bedrock](), [amazon-bedrock-data-automation](), [aws](), [aws-lambda](), [aws-step-functions](), [how-to](), [pii-redaction](), [pipeline](), [precision](), [serverless](), [technical-how-to]() ### AI overview This tutorial presents a serverless AWS pipeline for detecting and redacting personally identifiable information in scanned documents and images. It uses Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda, with a token-matching quality check to improve recall on degraded and handwritten documents. ### Source excerpt Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda. A custom blueprint redacts sensitive fields with field-level precision, and a token matching quality check raises recall across degraded and handwritten documents. ## AWS agents will suggest your new flights. Code decides what gets booked. DevFeed: [AWS agents will suggest your new flights. Code decides what gets booked.]() Original publisher: [Read original article]() Author: Meredith Shubel Published: 2026-09-15T21:27:21Z Content type: news Language: en Sources: [The New Stack]() Topics: [AWS Step Functions](), [Amazon Bedrock AgentCore](), [Orchestration](), [Generative AI](), [Amazon Web Services]() Tags: [ai-agents](), [ai-engineering](), [airline](), [amazon-bedrock-agentcore](), [aws](), [aws-step-functions](), [cloud-services](), [generative-ai](), [orchestration]() ### AI overview AWS published a Step Functions pattern for airline rebooking in which Amazon Bedrock AgentCore agents propose itineraries and compensation messages, while deterministic workflow steps validate proposals before reservations change or payments are issued. ### Source excerpt AWS published a new Step Functions pattern this week that gives AI agents a role in airline rebooking while keeping The post AWS agents will suggest your new flights. Code decides what gets booked. appeared first on The New Stack. ## Validating multi-agent decisions with Step Functions and Bedrock AgentCore DevFeed: [Validating multi-agent decisions with Step Functions and Bedrock AgentCore]() Original publisher: [Read original article]() Author: Ben Freiberg Published: 2026-09-14T16:47:23Z Content type: article Language: en Sources: [AWS Compute Blog]() Topics: [Amazon Bedrock AgentCore](), [AWS Step Functions](), [Artificial Intelligence](), [Generative AI](), [Automation]() Tags: [ai-agents](), [amazon-bedrock-agentcore](), [audit-trail](), [automation](), [aws-step-functions](), [generative-ai](), [regulatory](), [technical-how-to](), [workflow]() ### AI overview The article presents a pattern for validating multi-agent airline rebooking decisions. Amazon Bedrock AgentCore agents propose options, while AWS Step Functions applies deterministic validation, supports large-scale parallel processing, enables human review, and maintains an execution history for auditing. ### Source excerpt Orchestrating specialized Amazon Bedrock AgentCore agents with AWS Step Functions gives you the reasoning power of generative AI with the guardrails of deterministic validation. Agents propose options, and deterministic code validates them before any action is taken, demonstrated here with an airline rebooking workflow. ## Set up your AI coding agent to build with AWS Step Functions DevFeed: [Set up your AI coding agent to build with AWS Step Functions]() Original publisher: [Read original article]() Author: D Surya Sai Published: 2026-08-19T11:41:31Z Content type: release Language: en Sources: [AWS Compute Blog]() Topics: [AWS Step Functions](), [ai-coding](), [Model Context Protocol](), [Amazon Web Services](), [Serverless]() Tags: [ai-coding](), [announcements](), [aws](), [aws-step-functions](), [intermediate-200](), [mcp](), [serverless]() ### AI overview AWS Step Functions added a console button that provides a prompt for configuring compatible AI coding agents with Step Functions skills and an MCP server. The setup enables natural-language workflow development and AWS state-machine operations. ### Source excerpt AWS Step Functions has added a Copy agent prompt button to the console that configures your AI coding agent with Step Functions skills and an MCP server in one step. Paste the prompt into Claude Code, Kiro CLI, Cursor, or any MCP-compatible agent and start building workflows with natural language. ## Replacing AWS Step Functions with SQS FIFO queues and cutting the cost in half DevFeed: [Replacing AWS Step Functions with SQS FIFO queues and cutting the cost in half]() Original publisher: [Read original article]() Author: Alexei Liulin Published: 2025-03-14T14:47:27Z Content type: article Language: en Sources: [Homegate Engineering Blog - Medium]() Topics: [Amazon Simple Queue Service (SQS)](), [AWS Step Functions](), [Amazon Web Services]() Tags: [aws](), [aws-step-functions](), [batching](), [cloud-computing](), [cost](), [cost-optimization](), [email](), [fifo](), [lambda](), [notifications](), [push-notifications](), [queue](), [sqs](), [sqs-queue](), [workflow]() ### AI overview The article describes SMG Real Estate's Search Alerts system, which batches property-match notifications for delivery by email or mobile push notification. It explains the original AWS Step Functions implementation and its transition-cost problem, motivating a more cost-efficient approach using SQS FIFO queues. ### Source excerpt One of the core services for SMG Real Estate is Search Alerts -- a service that allows users to be notified about new properties published on ImmoScout24 and Homegate. For example, if a user is looking for a new apartment having N rooms and costing less than X, and not finding any matches now, they can create a search alert with those search criteria. When a new property matching those criteria is published, the user will be notified either via email or a mobile push notification. About the Search Alerts system Users can choose the frequency of notifications -- either every 5 minutes or every 4 hours (assuming there are any to be delivered). The vast majority of search alerts are configured with the 5-minute frequency. Just to get an idea of the scale, we have: Millions of published properties match saved search alerts every day More than a million emails and push notifications sent daily Check out our "Homegate's fast and modern search experience helps users find their dream home" blog post for an overview of how Search Alerts work. The Original Implementation In the original implementation we used an AWS Step Function to achieve the 5- minute batching of notifications: When a new property matching a search alert arrived, the StartSendNotificationProcess lambda would start a Step Function execution specific to that search alert. All it did was waiting for 5 minutes while the matches accumulated in the matches-{searchAlertId} SQS queue, which was programmatically created for that specific search alert If more matching listings arrived during the 5-minute waiting period, the StartSendNotificationProcess lambda attempted to start the step function execution with the same name. When it failed with the ExecutionAlreadyExists error, we knew there was already a SF for waiting. That way the deduplication of notification processes was guaranteed. After 5 minutes of waiting time, the Step Function execution proceeded with triggering the LoadMatches lambda that received the acc ## Automating the Klarna Card Ownership Fees System using AWS Step Functions DevFeed: [Automating the Klarna Card Ownership Fees System using AWS Step Functions]() Original publisher: [Read original article]() Author: Michel Neumann Published: 2024-05-02T07:42:27Z Content type: article Language: en Sources: [Klarna Engineering]() Topics: [AWS Step Functions](), [AWS CloudFormation](), [Automation](), [jira]() Tags: [athena](), [automation](), [aws](), [aws-step-functions](), [cloudformation](), [databases](), [jira](), [klarna](), [maintenance](), [pull-requests](), [run](), [serverless](), [step-functions](), [workflow]() ### AI overview The article explains how Klarna automated its Klarna Card monthly fee-collection process with AWS Step Functions and CloudFormation. The automation replaced a manual, multi-day batch workflow with a scheduled process and reduced maintenance effort. ### Source excerpt This article outlines how my team and I applied automation using AWS Step Functions and CloudFormation on a system to charge the monthly fee for Klarna Cards, enabling us to transform a previously manual routine into a self-sufficient, scheduled workflow. The initiative significantly streamlined operations and reduced maintenance cost. Introduction In early 2023, Klarna introduced monthly fees for Klarna Cards in the US. In the Card & Banking domain, two teams, including myself as engineer, developed this system within a tight four-month deadline. Initially, the system required extensive manual operation, including a detailed checklist for engineers to follow to ensure successful executions. The teams launched, planning iterative improvements of that routine. Months passed by without any advancement in refining the operation process nor automating any part of it. To provide an overview of what needed to be done by the teams to run the batch jobs: Designating an engineer to lead the monthly process, coordinated using JIRA tickets Updating exemption lists and submitting pull requests to the code-base prior to initiating batch runs Ensuring data integrity by performing Athena queries across three different production databases within the AWS Console Manually initiating multiple batch jobs in a specified sequence with manual input of arguments in a live production setting Awaiting termination of the jobs and conducting a thorough review of the outcomes of the final batch jobs for each market Overall, this routine took around three business days per month and required two engineers to approve code changes and review the results of the batch runs. Considering new markets where fees may be rolled out towards, this workflow posed a significant challenge to maintaining high-quality standards and preventing potential incidents. Taking on The Challenge We recognized that continuing with our current process was unsustainable and bound to cause issues down the line. When the top ## Accommodation Consolidation: How we created an ETL pipeline on cloud DevFeed: [Accommodation Consolidation: How we created an ETL pipeline on cloud]() Original publisher: [Read original article]() Author: Praneeth Peiris I want Published: 2020-03-26T00:00:00Z Content type: article Language: en Sources: [Trivago]() Topics: [AWS Glue](), [AWS Step Functions](), [etl](), [data](), [Cloud]() Tags: [aws](), [aws-glue](), [aws-step-functions](), [backend](), [batch](), [cloud](), [data](), [engineering-culture](), [etl](), [overhead](), [pipeline](), [pipelines]() ### AI overview trivago describes a hybrid AWS architecture using AWS Glue and AWS Step Functions to build ETL pipelines for consolidating frequently changing hotel information from hundreds of partners. The approach batches updates to reduce computational overhead and supports separately tested consolidation models and sandbox environments. ### Source excerpt Imagine you go to your hotel for check-in and they say that your dog is not allowed even though the website clearly states that it is!trivago gets information about millions of accommodat... ## Using the Serverless framework to deploy hybrid serverless/cluster workflows DevFeed: [Using the Serverless framework to deploy hybrid serverless/cluster workflows]() Original publisher: [Read original article]() Author: Rustem Feyzkhanov Published: 2019-05-20T00:00:00Z Content type: tutorial Language: en Sources: [Serverless Blog]() Topics: [Framework](), [serverless framework](), [AWS Lambda](), [AWS Step Functions](), [AWS Fargate](), [Amazon Web Services]() Tags: [aws](), [aws-fargate](), [aws-lambda](), [aws-step-functions](), [cloud-computing](), [engineering](), [faas](), [framework](), [function-as-a-service](), [infrastructure-as-code](), [serverless](), [serverless-architecture](), [serverless-framework]() ### AI overview This tutorial covers using Serverless Framework with AWS Lambda, AWS Step Functions, AWS Fargate, and AWS Batch to deploy hybrid serverless and cluster workflows. ### Source excerpt We'll cover how to use Serverless Framework, AWS Lambda, AWS Step Functions, AWS Fargate and AWS Batch to deploy hybrid serverless/cluster workflows. ## Circuit Breaker with AWS Step Functions DevFeed: [Circuit Breaker with AWS Step Functions]() Original publisher: [Read original article]() Author: Nikhil Kuriakose Follow Published: 2019-04-09T00:00:00Z Content type: tutorial Language: en Sources: [Trivago]() Topics: [AWS Step Functions](), [distributed-systems](), [Error Handling](), [Availability](), [Amazon Web Services]() Tags: [availability](), [aws-step-functions](), [backend](), [cloud](), [distributed-systems](), [error-handling](), [external](), [health](), [lambda](), [pipelines](), [services](), [state](), [workflows]() ### AI overview The article explains how trivago uses the circuit breaker pattern with AWS Step Functions to keep workflows responsive when external services are unresponsive, throttled, or return errors. It describes pausing calls, retrying selected failures, and modeling Lambda-based workflows as state machines. ### Source excerpt Many of our data pipelines interact with external services. The availability of an external service can adversly affect the health our pipelines. This is how we handle it using AWS Step Functions ## How to manage your AWS Step Functions with Serverless DevFeed: [How to manage your AWS Step Functions with Serverless]() Original publisher: [Read original article]() Author: Takahiro Horike Published: 2017-09-18T00:00:00Z Content type: tutorial Language: en Sources: [Serverless Blog]() Topics: [AWS Step Functions](), [Serverless]() Tags: [aws](), [aws-lambda](), [aws-step-functions](), [cloud-computing](), [engineering](), [faas](), [function-as-a-service](), [how-to](), [infrastructure-as-code](), [serverless](), [serverless-architecture](), [serverless-framework]() ### AI overview This tutorial explains how to manage complex workflows using Serverless and AWS Step Functions. ### Source excerpt Managing complex workflows with Serverless and AWS Step Functions. ## AWS Lambda Power Tuning with AWS Step Functions DevFeed: [AWS Lambda Power Tuning with AWS Step Functions]() Original publisher: [Read original article]() Author: Alex Casalboni Published: 2017-06-29T00:00:00Z Content type: article Language: en Sources: [Serverless Blog]() Topics: [AWS Lambda](), [AWS Step Functions](), [Amazon Web Services](), [Framework](), [Serverless]() Tags: [aws](), [aws-lambda](), [aws-step-functions](), [cloud-computing](), [engineering](), [faas](), [framework](), [function-as-a-service](), [infrastructure-as-code](), [serverless](), [serverless-architecture](), [serverless-framework]() ### AI overview Alex Casalboni presents a Serverless Service that uses AWS Step Functions and the Serverless Framework to optimize AWS Lambda function performance and costs. ### Source excerpt Alex Casalboni presents his Serverless Service powered by AWS Step Functions and the Serverless Framework to optimize your Lambda Functions performance and costs.